Google Cloud Big Data and Machine Learning Fundamentals
Outlines methods to determine main products, develop streaming pipelines, explore alternatives, and define essential steps for machine learning workflows on Google Cloud.
Tensorflow,Bigquery,Google Cloud Platform,Cloud Computing
Description for Google Cloud Big Data and Machine Learning Fundamentals
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud Training
Duration: 9 hours (approximately)
Schedule: Flexible
Pricing for Google Cloud Big Data and Machine Learning Fundamentals
Use Cases for Google Cloud Big Data and Machine Learning Fundamentals
FAQs for Google Cloud Big Data and Machine Learning Fundamentals
Reviews for Google Cloud Big Data and Machine Learning Fundamentals
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Google Cloud Big Data and Machine Learning Fundamentals
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world
Gain the skills needed for a machine learning engineering role and prepare for the Google Cloud Professional Machine Learning Engineer certification exam by learning to design, build, and productize ML models using Google Cloud technologies.
Gain practical experience in optimizing, deploying, and scaling machine learning models using Google Cloud Platform through a structured five-course specialization with hands-on labs and a focus on advanced topics and recommendation systems.
Construct and train neural networks and tree ensemble methods using TensorFlow, while applying effective machine learning practices for real-world data generalization.
Learn to develop, train, and assess neural networks using TensorFlow to resolve classification issues by understanding the fundamental principles of neural networks.
Learn to use Vertex AI on Google Cloud for no-code AutoML model development, training, and deployment, while integrating ML with cloud tools and adhering to Responsible AI principles.
Data Engineering on Google Cloud. Embark on a vocation in data engineering. Provide business value through the application of machine learning and big data.
Master the process of exploratory data analysis, train AutoML models with Vertex AI and BigQuery ML, optimize models using performance metrics and loss functions, and generate scalable datasets for training and evaluation.
Learn to load data, create features, and build and evaluate both supervised and unsupervised models in BigQuery for fraud and anomaly detection.
Featured Tools
Achieve a professional status as an AI Engineer. Acquire the knowledge necessary to develop next-generation applications that are propelled by generative AI, a skill that is indispensable for startups, agencies, and large corporations.
Delve into the historical evolution of Generative AI and AI, exploring diverse models and their applications in business contexts for optimized decision-making and innovation.
Explore the evolution and business implications of generative AI, emphasizing data significance, governance, transparency, and practical applications in modernization and customer service in this course.
Enhance your software development career with Gen AI. Develop hands-on, in-demand Generative AI skills to elevate your software engineering game in one month or less.
Acquire the knowledge necessary to direct your AI voyage. In this program, a CEO will instruct you on how to become a hands-on, AI-powered leader who is prepared to unlock the transformative potential of GenAI for your organization.